Search Results (638)

The factors affecting vultures’ space use can be complex, but food availability is often considered the primary determinant. However, when vultures’ food resources become highly predictable, their role in movement ecology has been little studied. Conservation planning for endangered vulture species requires a comprehensive understanding of space use. In this study, we quantified several metrics that may affect the space use of Cinereous Vultures (Aegypius monachus), a central-place forager isolated in the southeastern Balkans, which had access to substantial artificially provided food (33 tons per year) during the study period (2004–2009). Metrics examined for putative influence on ranging behavior included season, age, sex, breeding status, and artificially provided food quantity. Home range and core area sizes were larger during the breeding season and smaller during the non-breeding season. Although age, sex, and breeding status did not affect space use, we found strong evidence that artificially provided food predictability can shape the movement ecology of Cinereous Vultures. Annual home range size, core area, and seasonal overlap of the spatial parameters did not vary greatly over the years, suggesting repeatability in the species’ ranging behavior. Highly predictable artificially provided food can modify the movement ecology of necrophagous species. Yet, providing safe food is essential to preserve this endangered vulture. We suggest that feeding programs be gradually diversified to simulate natural carrion availability by using multiple small feeding sites and supplementing them unpredictably with small amounts of food. Full article

Pollination services provided by insects are fundamental to the productivity and quality of sweet cherry orchards. This study investigated the flower-visiting insect community and compared the pollination potential of A. mellifera and A. cerana in a sweet cherry orchard on the Loess Plateau of eastern Gansu, China. Field surveys were conducted during the blooming periods of 2025 and 2026. Visual observation and video recording documented flower-visiting insects across five daily time intervals. Foraging behavior, including flower-handling time and inter-visit interval, was measured in both bee species. Pollen loads on five body parts (head, thorax, abdomen, wings, and legs) were measured by hemocytometry. Standing nectar volume was measured by capillary extraction. Statistical analyses included generalized linear models, Friedman tests, and Pearson correlation analysis. Fourteen insect taxa were identified, among which Hymenoptera was the most dominant order. The main visitors were A. mellifera and A. cerana. The peak of A. cerana visitation was at 12:00–14:00, whereas A. mellifera showed a broader activity peak spanning 12:00–16:00. Apis mellifera exhibited a significantly longer single-flower handling time compared to A. cerana, and inter-visit intervals did not differ significantly between species. Pollen loads showed both species carried the loosest pollen on their legs, but A. cerana also maintained a substantial load on its thorax. Pollen loads did not differ significantly between the two species on any body region. Pollinator activity and standing nectar volume both peaked at 14:00–16:00, but bee visitation showed no linear correlation with environmental factors. Although A. mellifera was numerically dominant, our findings indicate that A. cerana may play a disproportionate role in pollination because of its unique pollen-carrying profile and earlier peak of activity. Therefore, maintaining both honeybee species alongside a diverse assemblage of flower-visiting insects is a prudent strategy for resilient orchard pollination. Full article

The Argentine ant, Linepithema humile (Mayr), is an important invasive pest in natural, agricultural, and urban ecosystems worldwide. Boric acid and thiamethoxam have been used as bait toxicants for Argentine ant management. Most of the toxicological investigations on these toxicants have focused on the mortality of the ants. However, their behavioral effects on target ants remain poorly understood. By focusing on the in-nest aggregation and out-nest activity level, the current study investigated the behavioral effects of low concentrations of boric acid and thiamethoxam on Argentine ants. Boric acid increased in-nest aggregation and reduced activity in the foraging area. In contrast, thiamethoxam treatment caused the ants to leave the nest and continue roaming in the foraging area. Individual behavior assay showed that overall mobility of ants was not impacted by any of the treatments, while thiamethoxam treatment caused ants to spend more time in the lighted area. Distinct behavioral impacts of these toxicants might be due to differences in their unique modes of actions. Understanding these behavioral effects of bait toxicants would help to optimize management protocols for the Argentine ant. Full article

The collection of honey and propolis is crucial for the nutrition and health of honey bee colonies. In this study, Apis mellifera with high productivity for both honey and propolis (MJ) was developed through long-term selective breeding using Apis mellifera caucasica and Apis mellifera carnica as breeding materials, resulting in substantial improvements in both honey yield and propolis production. To elucidate the genetic basis and molecular mechanisms underlying efficient foraging behavior for nectar and resins in honey bees, whole-genome resequencing was performed on MJ, the C-lineage, and the O-lineage of Apis mellifera. In addition, transcriptome sequencing was conducted using MJ and Apis mellifera ligustrica, which exhibited the highest honey and propolis production traits. MJ had a composite genetic background dominated by O-lineage ancestry. Compared with C-lineage honey bees, MJ exhibited 234 candidate genes under selection, mainly related to chitin and amino sugar metabolism. Transcriptome analysis identified 504 and 2676 differentially expressed genes between MJ and Italian honey bees in the nectar-forager and resin-forager comparisons, respectively, involving chemosensory gene families. Genes upregulated in MJ nectar and resin foragers were mainly associated with redox regulation and energy metabolism, respectively. Integrated analyses identified 7 candidate genes associated with nectar foraging and 41 candidate genes associated with resin foraging; these genes were involved in chemosensory responsiveness, flight-related structural traits, energy metabolism, and redox regulation in MJ. These findings provide genetic and transcriptomic resources for further studies on the division of labor in foraging and molecular breeding in honey bees. Full article

High-altitude animals rely on vertical spatial adaptation to cope with harsh environments, yet the underlying drivers of their seasonal altitudinal distribution remain poorly understood. This study investigated how solar radiation, seasonal high-quality food resources and stable foods shape the altitudinal distribution of the highest-altitude primate Rhinopithecus bieti, to uncover its survival strategies. Through systematic environmental data collection and three-year field tracking of a wild group in the Lasha Mountains, northwest Yunnan, China, we identified consistent seasonal patterns: spring in low-altitude habitats, summer at highest elevations, and intermediate ranges during autumn/winter. Statistical modeling revealed seasonally shifting environmental dependencies. Summer showed no resource limitations, while autumn introduced solar exposure and mature leaves as positive synergistic factors (50% model explanatory power). Winter exhibited peak environmental pressure (80%), with solar and buds becoming critical, though revealing a trade-off between foraging and thermoregulation. Spring demonstrated the strongest environmental coupling (86%), where solar and high-quality food showed significant positive synergy, enabling physical recovery. The species displays remarkable ecological plasticity, with solar being the core cold-season driver. The winter-to-spring transition from resource trade-off to synergy reflects dynamic behavioral adaptations to seasonal climate and nutritional bottlenecks, offering new insights into primate survival strategies in extreme environments. Full article

The rapid development and expansion of the Internet of Things (IoT) ecosystem require managing increasing computational demands with the aid of advanced hierarchical architectures. The integration of a complete four-tier hierarchy—including Mobile, Edge, Fog, and Cloud layers—and the priority requirements are being overlooked in the literature despite the effort of existing studies. The goal of this study is to fill these gaps by proposing a novel, context-aware task-offloading framework designed for multi-dimensional ecosystems involving multi-server and multi-application environments. A targeted biomimetic approach is utilized at the core of this research. The decentralized foraging behavior of biological swarms is translated into a concrete engineering solution. This solution is designed specifically for computational offloading and resource management. To achieve this, a “Learning-guided Meta-heuristic” hybrid model is developed. Within this framework, bio-inspired Ant Colony Optimization (ACO) is directly integrated with an Upper Confidence Bound (UCB)-inspired exploration mechanism. Natural, pheromone-based imitation is solely relied upon by traditional biomimetic algorithms. In contrast, higher-order cognitive learning is fully incorporated by this hybrid synergy. Consequently, underlying system dynamics are adaptively learned. Local minima traps are also successfully avoided. This avoidance is achieved by dynamically selecting the optimal layer for each individual task. Both energy consumption and latency are optimized simultaneously. Meanwhile, strict operational feasibility is ensured through a dynamic penalty-based mechanism. Battery and deadline constraints are explicitly handled by this mechanism. Extensive simulations demonstrate the superiority of the proposed UCB-ACO model over state-of-the-art meta-heuristics, including Particle Swarm Optimization (PSO), Gray Wolf Optimizer (GWO), ACO, Artificial Bee Colony Optimization (ABO), and Non-dominated Sorting Genetic Algorithm II (NSGA-II). The findings reveal that the proposed framework outperforms the methods compared by achieving 22.5% lower latency and 23% lower energy consumption. This study effectively maps the current literature and then introduces a pioneering solution for next-generation resource management in distributed computing. Full article

As integral components of ecosystems, rodents exhibit high sensitivity to environmental fluctuations. As a typical semi-subterranean rodent, the burrowing and foraging behaviors of the mole vole (Ellobius tancrei) profoundly impact local microhabitat structure and vegetation succession. Given its extensive distribution range, investigating the geographical distribution of the mole vole under climate change is critical for understanding its population dynamics and spatial patterns. To explore the impacts of climate change on the potential distribution of this species, we utilized an ensemble model based on 395 occurrence records and 38 environmental variables. We predicted its potential geographical distribution under current (1970–2000) and three future climate scenarios (SSP126, SSP245, and SSP585) across three future periods (2041–2060, 2061–2080, and 2081–2100) and further analyzed the variation trends and centroid migration directions of its global potential distribution. The results revealed the following: (1) Elevation (Dem) and temperature annual range (Bio7) were the dominant environmental factors driving the potential distribution of the mole vole, followed by precipitation of the warmest quarter (Bio18), mean diurnal range (Bio2), annual mean temperature (Bio1), base saturation (BSAT), precipitation seasonality (Bio15), calcium carbonate content (TCARBON_EQ), and available water capacity (AWC). (2) Under current climate conditions, the highly suitable habitats were mainly concentrated in Eurasia, particularly in Turkey, Kyrgyzstan, China, Mongolia, and Russia. (3) Under future climate scenarios, suitable habitats showed simultaneous expansion and contraction, with expansion consistently exceeding contraction across all scenarios and periods, especially under SSP585 in the late 21st century. (4) Relative to the current period, the suitable-habitat centroid shifted northeastward under SSP126, but northwestward under SSP245 and SSP585. This study reveals the dynamic spatial shifts of the mole vole driven by climate change, not only providing crucial scientific support for early spatial warning and precise prevention of agricultural and pastoral rodent damage, but also laying a theoretical foundation for understanding the ecological adaptation mechanisms of subterranean rodents and mitigating potential cross-regional dispersal risks. Full article

Hippodamia variegata is a key natural enemy of various aphid pests in agricultural ecosystems, and its foraging and oviposition behaviors are strongly dependent on chemical signals from prey aphids and host plants. In this study, we functionally characterized the chemosensory protein HvarCSP8 to elucidate its potential role in mediating olfactory responses to aphid-induced plant volatiles. The expression profiles of HvarCSP8 were examined by quantitative real-time PCR (qRT-PCR) across developmental stages and sexes; the recombinant HvarCSP8 was purified; the potential ligands specificity and affinity were studied using fluorescence-based competitive binding assays; and structural characteristics were obtained via homology modeling and molecular docking simulations. The results demonstrated that HvarCSP8 exhibits pronounced sex- and tissue-specific expression, with significant upregulation in adult antennae, particularly in females. The purified protein exhibited selective binding affinity to multiple aphid-induced plant volatiles, such as α-Farnesene, α-Terpinene, and 2-Ethyl-1-hexanol. Molecular docking revealed that HvarCSP8 interacts with these ligands through multiple amino acid binding sites, among which hydrophobic residues such as VAL29, LEU61, ILE64, and LEU65 frequently occur in binding sites for multiple ligands, suggesting that these residues play important roles in binding. These findings indicate that HvarCSP8 may be involved in the olfactory detection of aphid-induced plant volatiles in H. variegata, providing a candidate target for the development of behavior-based biological control strategies against aphid pests. Full article

The flatfish Citharichthys spilopterus is a common predatory species in the estuaries of the southwestern Gulf of Mexico. In general, factors controlling the foraging behavior of fish can be extrinsic (environmental conditions) or intrinsic (size-related differences). The main objective of this study was to analyze spatiotemporal and body size-related variations in the diet of this species and their coupling with main environmental conditions. Every two months, 24 h sampling cycles were conducted in two habitats, one with submerged vegetation and the other without vegetation. Fish were collected every 2 h during each cycle. Canonical correspondence analysis revealed that submerged vegetation and body size were the main factors influencing diet composition, while diurnal variation was not significant. Decapod larvae and copepods were consumed more frequently in the unvegetated habitat during the dry season and by smaller fish, while peracarids, shrimp, and fish were consumed more frequently in the vegetated habitat during the rainy season and by larger fish. PERMANOVA analysis detected significant differences in diet between size groups, habitats, and months. Similarly, the fullness index showed significant differences between size groups and months. These spatiotemporal and ontogenetic trophic changes reflect the adaptation processes of the species to the seasonal and spatial environmental variability of the system. Full article

Heat stress is a growing concern in cattle production systems due to the increasing frequency and intensity of extreme weather events driven by climate change. This review synthesizes current knowledge on the multifaceted impacts of heat stress and focuses on nutritional strategies to mitigate its effects on ruminating cattle. A comprehensive literature search was conducted using PubMed, Scopus, Web of Science, and Google Scholar. Heat stress adversely affects cattle physiology, behavior, rumen function, and overall productivity, particularly in dairy animals with high metabolic activity. During heat stress episodes, changes in the microbial population have been reported; however, there is no clear consensus, as findings vary widely among studies depending on diet, feed intake, animal type and experimental design. This variability limits the ability to draw general conclusions regarding changes in the rumen microbiome driven by heat stress. In this context, dietary nutritional intervention strategies offer a practical and scalable approach to enhance thermotolerance and maintain performance under heat stress conditions. Key nutritional strategies include modifications in diet composition to reduce metabolic heat production, with some approaches carrying potential risks to animal health, e.g., increasing dietary energy density through concentrates while minimizing forage content. Supplementation with rumen-protected nutrients like amino acids, vitamins, and minerals can be used to support immune function, antioxidant capacity, and metabolic stability. Polyphenols and betaine contribute to oxidative stress reduction and gut integrity, while probiotics may be used to improve rumen fermentation and nutrient utilization. Sensor technologies, including rumen boluses and wearable devices, offer the potential to monitor physiological responses to heat stress in real time and offer opportunities for precision feeding and early intervention. Most published studies only cover short periods of heat stress, and there is a lack of in vitro models simulating rumen hyperthermia. In parallel, future research should therefore prioritize longitudinal, in vivo trials that integrate physiological, metabolic, and microbial responses to understand the long term and systemic effect of heat stress. In addition, controlled trials in commercial settings are necessary to prove the transferability of results to commercial herds. A multidisciplinary approach combining nutritional, environmental, and technological strategies is likely to play an important role in safeguarding cattle welfare and productivity in a warming climate. Full article

In this study, we present a novel adaptive algorithm, social learning-enhanced deep reinforcement learning (SLDRL), which integrates social learning mechanisms into deep reinforcement learning (DRL) to improve agent performance in both discrete and continuous state-space environments. The proposed hybrid control architecture enables agents to autonomously decide when and how to exploit socially acquired behaviors, balancing social learning with individual exploration through an entropy-based intrinsic motivation mechanism. The framework incorporates online imitation and enactment mechanisms that allow agents to observe and selectively reuse behavioral sequences acquired from other agents during training. We evaluate SLDRL in a sparse-reward discrete grid-based foraging task and in the dense-reward continuous-state/discrete-action CartPole problem. In both domains, SLDRL agents outperform baseline DRL agents, achieving faster learning and higher cumulative rewards. The results show that socially acquired behaviors are utilized adaptively throughout training, with the balance between imitation and individual learning emerging dynamically according to the structure of the environment and the agent’s experience. Comparisons with a behavioral cloning baseline further indicate that selectively integrating observed behaviors can yield more robust long-term learning than direct imitation of demonstration trajectories. Overall, the results demonstrate that SLDRL can effectively leverage online social learning in diverse environments. Full article

Gustatory perception in honeybees is a key determinant of foraging decisions and pollen source selection. However, the molecular mechanisms underlying this sensory discrimination remain poorly understood. To investigate these mechanisms during the collection of pollen from different floral sources, this study utilized antennae from worker bees foraging on pear and rapeseed pollen, and non-pollen-foraging workers as controls. Illumina high-throughput transcriptome sequencing was employed to identify differentially expressed genes (DEGs), perform functional annotation, and characterize gustatory receptor (GR) genes. Compared with the control group, 583 DEGs and 516 DEGs were identified in pear-pollen and rapeseed-pollen foragers, respectively, whereas only 73 DEGs were detected between the two pollen-foraging groups. Several DEGs were associated with chemosensory perception, signal transduction, energy metabolism, and immune responses. Notably, genes involved in membrane-associated signaling and stimulus response exhibited differential expression patterns among foraging groups, suggesting adaptive molecular responses to distinct floral resources. Gene Ontology (GO) analysis indicated that DEGs were primarily associated with cellular processes, membrane components, and binding functions. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment highlighted significant involvement in phagosome, phosphatidylinositol signaling system, oxidative phosphorylation, and extracellular matrix–receptor interaction. Notably, seven GR-related genes were identified in the antennal transcriptome, including five known GR genes and two novel candidates, all with complete open reading frames. Four of these genes featured the canonical seven-transmembrane domain structure of insect GRs. Phylogenetic analysis, in addition to the known sugar receptors AmelGR43a, AmelGR64f, and AmelGR64f-X1, based on GRs from Apis mellifera and Drosophila melanogaster suggested that AmelGR28b, AmelGR10, AmelGR12, and AmelGR13 may belong to the bitter taste receptor family. Quantitative real-time PCR (qRT-PCR) validation demonstrated that the expression patterns of the selected seven DEGs were consistent with the RNA-seq results. This study reveals differential expression patterns and potential functional divergence of gustatory receptor genes in Apis mellifera during pollen collection from different floral sources. It provides important molecular evidence for understanding how honeybees accurately recognize and preferentially forage specific pollen sources via gustatory perception, and offers valuable theoretical and practical insights for honeybee behavioral ecology and crop pollination management. Full article

Virtual fencing is increasingly used in grazing systems as a flexible alternative to physical fencing, yet detailed assessments of cattle behavior within such systems remain limited. This study investigates the use of collar-mounted tri-axial accelerometers combined with supervised machine learning to characterize cattle behavior in a virtual fencing system. Seven free-ranging Angus cattle were monitored using accelerometers mounted on a virtual fencing system, GNSS positioning, and virtual fence warning logs. A random forest classifier was developed and trained to identify key behaviors (grazing/feeding, ruminating, lying, standing and locomotion) using features derived from tri-axial accelerometer data. The model achieved high classification performance for grazing/feeding, ruminating, and lying (mean accuracy = 0.87, range = 0.83–0.90), enabling estimation of individual behavioral time budgets. Daily activity patterns were generally stable over time and across individuals. Spatial analyses revealed significant differences in behavior between areas near the virtual fence boundary and interior pasture locations, with increased grazing and reduced ruminating near the boundary, potentially reflecting spatial variation in habitat type or forage availability. In the virtual fencing system, cattle are equipped with collars that emit an auditory warning when they approach a virtual boundary, followed by a low-energy electrical impulse when the warning is ignored over a directional distance of 5–10 m. Event-based analyses showed no consistent short-term changes in either movement intensity and direction nor locomotion following auditory warning events, indicating that cattle habituated to the system did not exhibit uniform behavioral disturbance in response to warnings. These results suggest that accelerometer-based behavior classification can provide fine-scale, non-invasive insights into spatio-temporal cattle behavior in virtual fencing systems. The finding indicates that, in a habituated herd, virtual fencing was not associated with pronounced disruption to the measured behavioral patterns, while highlighting the potential of embedded sensor data for animal-based behavioral monitoring. Full article

This study proposes a stochastic time-delay pheromone feedback model to describe ant foraging dynamics, and investigates how response delays and environmental noise jointly induce stochastic oscillations and reorganize the system’s probabilistic structure. By employing near-Hopf center-mode projection and stochastic averaging, we derive the first-order stochastic amplitude equation and analyze the stochastic dynamical properties near the deterministic delay-induced Hopf bifurcation. Subsequently, normalized Shannon entropy and Jensen–Shannon divergence, computed relative to a pre-Hopf stochastic stationary reference distribution, are used to quantify uncertainty expansion and distributional reorganization in the stationary amplitude distribution and reconstructed state-variable distributions. The analytical results are supported by numerical simulations, which indicate that response delay primarily determines the transition from stable foraging to oscillatory behavior, while noise intensity mainly affects the dispersion and uncertainty of the amplitude distribution. Information-theoretic metrics further reveal noise-induced uncertainty growth and delay-induced probabilistic restructuring. This study elucidates the stability regulation mechanisms of ant foraging systems under stochastic conditions from a combined dynamical and information-theoretic perspective, and provides a theoretical reference for the design of delayed feedback in swarm intelligence systems. Full article

Industrial contamination can influence the transfer of toxic and essential elements through soil–plant–animal systems and may pose risks to food safety. This study aimed to determine whether contamination patterns in soil are reflected in forage vegetation and meat products and to evaluate trace-element behavior across interconnected components of the soil–plant–animal system. This study assessed the distribution and transfer of 12 elements (As, Be, Cd, Co, Cr, Cu, Hg, Mn, Ni, Pb, V, and Zn) in soil, forage vegetation, and meat products from five industrially affected areas of Central Kazakhstan. Element concentrations were determined by inductively coupled plasma mass spectrometry. Soil contained the highest concentrations of most elements, confirming its role as the primary reservoir of contamination, whereas forage vegetation reflected local pollution patterns. The highest levels of contamination were generally observed in the industrial centers of Temirtau and Zhezkazgan, with Zhezkazgan exhibiting the most distinct element profile. Soil-to-forage transfer was most pronounced for Cd, Cu, Pb, and Zn, with significant positive relationships between soil and forage concentrations (p < 0.001). Meat products generally contained lower element concentrations than soil and forage; however, Cd, Hg, and As exceeded regulatory limits in 23 of 279 samples (8.2%). By integrating environmental and animal-derived matrices within a single framework, this study provides new insight into trace-element transfer pathways and facilitates the identification of priority contaminants, high-risk areas, and livestock products requiring enhanced environmental and food safety monitoring in industrial regions. Full article